# Apple App Store Scraper + AI (`lizzyyy2/apple-app-store-scraper-ai`) Actor Scrape iOS app data, ratings and reviews from the Apple App Store, then optionally turn them into AI insights: review theme summaries, sentiment, and ASO keyword suggestions. No API key needed. - **URL**: https://apify.com/lizzyyy2/apple-app-store-scraper-ai.md - **Developed by:** [Lizzy](https://apify.com/lizzyyy2) (community) - **Categories:** Developer tools, AI - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Apple App Store Scraper + AI Scrape **iOS app data, ratings and customer reviews** from the Apple App Store — then optionally turn them into **AI insights** that most scrapers don't give you: summarized review themes, sentiment breakdowns, App Store Optimization (ASO) suggestions, and a competitor report. No API key, no login, no proxies. The scraper uses Apple's fast, public iTunes endpoints, and the AI runs on a built-in model (billed as platform usage) — **you don't need to bring your own AI key**. ### Why this Actor Most App Store scrapers stop at raw data. This one goes a step further: it reads the reviews *for* you and tells you what users actually love, hate, and want — and how to optimize your listing. - 🍎 **Reliable** — pure public iTunes API, no brittle HTML parsing. - ⚡ **Fast** — JSON endpoints, no browser rendering. - 🌍 **150+ storefronts** — any App Store country. - 🤖 **AI insights (optional)** — review analysis, ASO, competitor report. - 💸 **Pay only for what you use** — cheap base scraping, premium per AI insight. ### What you can do with it - **App developers** — see exactly what reviewers complain about and request. - **ASO / marketing teams** — get keyword and listing suggestions in seconds. - **Market researchers** — compare competitors and spot gaps. - **Investors / analysts** — track ratings, pricing and positioning across a category. ### Input | Field | Type | Description | |---|---|---| | `searchTerms` | array | Keywords to search the App Store (e.g. `meditation`). | | `appIds` | array | Specific app IDs or App Store URLs to scrape directly. | | `country` | string | Two-letter storefront code (`us`, `gb`, `de`, `tr`, …). Default `us`. | | `maxAppsPerTerm` | integer | Max apps per search term (1–200). Default 25. | | `includeReviews` | boolean | Fetch customer reviews. Default `true`. | | `maxReviewsPerApp` | integer | Max reviews per app (Apple caps ~500). Default 100. | | `aiEnrichment` | boolean | Master switch for AI insights. Default `false`. | | `aiReviewSummary` | boolean | AI review analysis (sentiment, complaints, praises, requests). | | `aiAso` | boolean | AI ASO suggestions (title, subtitle, keywords, description). | | `aiCompetitorReport` | boolean | One AI market report comparing all scraped apps. | | `aiLanguage` | string | Language for AI output. Default `English`. | #### Example input ```json { "searchTerms": ["meditation"], "country": "us", "maxAppsPerTerm": 10, "includeReviews": true, "maxReviewsPerApp": 100, "aiEnrichment": true, "aiReviewSummary": true, "aiAso": true, "aiLanguage": "English" } ```` ### Output One row per app, plus an optional `competitor_report` row. Each app row includes core metadata, the fetched reviews, and any AI insights you enabled: ```json { "recordType": "app", "appId": 1063171574, "appName": "Calm", "sellerName": "Calm.com, Inc.", "primaryGenre": "Health & Fitness", "price": 0, "averageRating": 4.79, "ratingCount": 1700000, "url": "https://apps.apple.com/us/app/calm/id571800810", "reviewsCount": 100, "aiSentiment": { "positive": 72, "neutral": 14, "negative": 14 }, "aiTopComplaints": ["Subscription auto-renew confusion", "Too many paywalls"], "aiTopPraises": ["Sleep stories", "Calming voices"], "aiFeatureRequests": ["Offline mode", "Family plan"], "aiReviewSummary": "Users love the sleep content and narration...", "aiAso": { "suggestedTitle": "Calm: Sleep & Meditation", "keywords": ["sleep", "meditation", "relax", "anxiety", "..."] } } ``` ### Pricing This Actor uses **pay-per-event** pricing: | Event | What it covers | |---|---| | App / review result | Each app and review row scraped (cheap). | | AI review analysis | Per app analyzed with AI. | | AI ASO suggestions | Per app with ASO suggestions. | | AI competitor report | Once per run. | You only pay for the AI features you turn on. Leave AI off and it's a fast, low-cost App Store data scraper. ### FAQ **Do I need an OpenAI/AI API key?** No. The AI runs on a built-in model billed as platform usage. **Where do reviews come from?** Apple's public customer-reviews RSS feed (most recent first), which caps at roughly 500 reviews per app per storefront. **Is this affiliated with Apple?** No. It only reads publicly available data. ### Related Actors — build a full pipeline Combine Actors to go from app research to outreach: - **App research → publisher outreach:** Use this Actor to find apps and their publishers in a category, then feed the publisher domains into the **AI Lead Enricher** to get emails, socials and a personalized opener — ideal for SDKs, monetization tools and agencies selling to app studios. - **Spot buying signals:** Pair with **Hiring Signals — Job Board Scraper + AI** to see which app companies are scaling their team (a strong spend signal) before you reach out. > Workflow: **App Store Scraper (targets)** → **AI Lead Enricher (contact + opener)** → your CRM. # Actor input Schema ## `searchTerms` (type: `array`): Keywords to search the App Store for (e.g. "meditation", "budget tracker"). The actor collects the top matching apps for each term. ## `appIds` (type: `array`): Specific apps to scrape directly. Accepts numeric App Store IDs (e.g. 1459969523) or full App Store URLs (e.g. https://apps.apple.com/us/app/headspace/id493145008). ## `country` (type: `string`): Two-letter App Store country code (e.g. us, gb, de, tr). Determines pricing, language and which storefront is queried. ## `maxAppsPerTerm` (type: `integer`): Maximum number of apps to collect for each search term (1-200). ## `includeReviews` (type: `boolean`): Fetch customer reviews (rating, title, text, author, date) for each app. Required for AI review analysis. ## `maxReviewsPerApp` (type: `integer`): Maximum number of reviews to fetch per app (Apple's public feed caps at ~500). ## `aiEnrichment` (type: `boolean`): Use a built-in AI model to analyze each app. Charged per AI insight generated. Turn on the specific tasks below. No API key required from you. ## `aiReviewSummary` (type: `boolean`): Summarize each app's reviews into sentiment breakdown, top complaints, top praises and requested features. Requires reviews to be scraped. Only runs when AI insights are enabled. ## `aiAso` (type: `boolean`): Generate App Store Optimization suggestions per app: optimized title, subtitle, keyword list and an improved description. Only runs when AI insights are enabled. ## `aiCompetitorReport` (type: `boolean`): Generate one market analysis comparing all scraped apps (positioning, strengths/weaknesses, opportunities). Saved to the key-value store and added as a dataset row. Charged once per run. Only runs when AI insights are enabled. ## `aiLanguage` (type: `string`): Language for AI-generated output (e.g. English, German, Turkish). ## Actor input object example ```json { "searchTerms": [ "meditation" ], "country": "us", "maxAppsPerTerm": 25, "includeReviews": true, "maxReviewsPerApp": 100, "aiEnrichment": false, "aiReviewSummary": true, "aiAso": false, "aiCompetitorReport": false, "aiLanguage": "English" } ``` # Actor output Schema ## `apps` (type: `string`): App records (with reviews and optional AI insights) in the default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchTerms": [ "meditation" ] }; // Run the Actor and wait for it to finish const run = await client.actor("lizzyyy2/apple-app-store-scraper-ai").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchTerms": ["meditation"] } # Run the Actor and wait for it to finish run = client.actor("lizzyyy2/apple-app-store-scraper-ai").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchTerms": [ "meditation" ] }' | apify call lizzyyy2/apple-app-store-scraper-ai --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lizzyyy2/apple-app-store-scraper-ai", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apple App Store Scraper + AI", "description": "Scrape iOS app data, ratings and reviews from the Apple App Store, then optionally turn them into AI insights: review theme summaries, sentiment, and ASO keyword suggestions. No API key needed.", "version": "0.1", "x-build-id": "6XAD4hdkVMfT6ztyX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lizzyyy2~apple-app-store-scraper-ai/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lizzyyy2-apple-app-store-scraper-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lizzyyy2~apple-app-store-scraper-ai/runs": { "post": { "operationId": "runs-sync-lizzyyy2-apple-app-store-scraper-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lizzyyy2~apple-app-store-scraper-ai/run-sync": { "post": { "operationId": "run-sync-lizzyyy2-apple-app-store-scraper-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchTerms": { "title": "Search terms", "minItems": 0, "type": "array", "description": "Keywords to search the App Store for (e.g. \"meditation\", \"budget tracker\"). The actor collects the top matching apps for each term.", "items": { "type": "string" } }, "appIds": { "title": "App IDs or App Store URLs", "minItems": 0, "type": "array", "description": "Specific apps to scrape directly. Accepts numeric App Store IDs (e.g. 1459969523) or full App Store URLs (e.g. https://apps.apple.com/us/app/headspace/id493145008).", "items": { "type": "string" } }, "country": { "title": "Country / storefront", "type": "string", "description": "Two-letter App Store country code (e.g. us, gb, de, tr). Determines pricing, language and which storefront is queried.", "default": "us" }, "maxAppsPerTerm": { "title": "Max apps per search term", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of apps to collect for each search term (1-200).", "default": 25 }, "includeReviews": { "title": "Scrape reviews", "type": "boolean", "description": "Fetch customer reviews (rating, title, text, author, date) for each app. Required for AI review analysis.", "default": true }, "maxReviewsPerApp": { "title": "Max reviews per app", "minimum": 0, "maximum": 500, "type": "integer", "description": "Maximum number of reviews to fetch per app (Apple's public feed caps at ~500).", "default": 100 }, "aiEnrichment": { "title": "Enable AI insights", "type": "boolean", "description": "Use a built-in AI model to analyze each app. Charged per AI insight generated. Turn on the specific tasks below. No API key required from you.", "default": false }, "aiReviewSummary": { "title": "AI review analysis", "type": "boolean", "description": "Summarize each app's reviews into sentiment breakdown, top complaints, top praises and requested features. Requires reviews to be scraped. Only runs when AI insights are enabled.", "default": true }, "aiAso": { "title": "AI ASO suggestions", "type": "boolean", "description": "Generate App Store Optimization suggestions per app: optimized title, subtitle, keyword list and an improved description. Only runs when AI insights are enabled.", "default": false }, "aiCompetitorReport": { "title": "AI competitor report", "type": "boolean", "description": "Generate one market analysis comparing all scraped apps (positioning, strengths/weaknesses, opportunities). Saved to the key-value store and added as a dataset row. Charged once per run. Only runs when AI insights are enabled.", "default": false }, "aiLanguage": { "title": "AI output language", "type": "string", "description": "Language for AI-generated output (e.g. English, German, Turkish).", "default": "English" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```